def dispim(imname='',subplot=111,chan=0, vmin=0.0, vmax=1.0): print 'Opening', imname ia.open(imname) pix = ia.getchunk() ia.close() vmin=0.0 vmax=1.0 if imname.count('mosaic')==0: arr = pix[:,:,0,chan] else: arr = pix[350:1150, 350:1150, 0, chan] if imname.count('sdonly')>0: vmax=5.0 if imname.count('alpha')==0: pl.imshow(pl.rot90( np.sign(arr)*np.sqrt(np.fabs(arr)) ), interpolation=None,cmap='jet',vmin=vmin, vmax=vmax) else: pl.imshow(pl.rot90( arr ), interpolation=None,cmap='jet',vmin=-3.0, vmax=1.0) # pl.imshow(pl.rot90(pix[:,:,chan,0]), interpolation=None,cmap='jet') pl.colorbar()
def triangleImage(link, nom, s): a = seuil(imageio.imread(link), s) a = py.rot90(a, 3) xBis, yBis = transforme(a.tolist()) xBis, yBis = np.array(xBis), np.array(yBis) cens, edg, tri, neig = triang.delaunay(xBis, yBis) taille = len(a.tolist()) l = taille / 15 b = 0 py.figure() for t in tri: # t[0], t[1], t[2] are the points indexes of the triangle d1, d2, d3 = d(xBis[t[0]], yBis[t[0]], xBis[t[1]], yBis[t[1]]), d(xBis[t[1]], yBis[t[1]], xBis[t[2]], yBis[t[2]]), d(xBis[t[2]], yBis[t[2]], xBis[t[0]], yBis[t[0]]) if (d1 < l and d2 < l and d3 < l): #t_i = [t[0], t[1], t[2], t[0]] t_i = [t[0], t[1], t[2], t[0]] if (b): py.fill(xBis[t_i], yBis[t_i], "black") b = 0 else: b = 1 py.savefig(nom)
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=60): [dimy,dimx] = pattern.shape mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius) #mask[518:518+slit,:] = 0 #mask[370:480,520:650] = 0 #mask[:370,520:580] = 0 #mask[590:600,505:515] = 0 crosswidth = 10 shiftx = 10 shifty = 5 mask[512-crosswidth+shiftx:512+crosswidth+shiftx, :] = 0 mask[:, 512-crosswidth+shifty:512+crosswidth+shifty] = 0 mask[470:512, 400:512] = 0 mask = fliplr(rot90(mask,3)) H = numpy.array([map(float,line.strip('\n').split(',')) for line in filterwindow.split('\n')]) blurred = imfilter(mask,H) newMask = 1-(blurred<0.99) H2 = H newMask = imfilter(newMask.astype('double'), H2) #newMask = imfilter(newMask.astype('double'), H2) mask *= newMask gMask = gaussian_mask(dimx,dimx,400,700,300) centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),90) return mask, gMask, centerMask
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=17): print 'getting shape' [dimy,dimx] = pattern.shape print 'mask bad areas' mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius) mask[518:518+slit,:] = 0 mask[370:480,520:650] = 0 mask[:370,520:580] = 0 mask[590:600,505:515] = 0 print 'doint some flipping...' mask = fliplr(rot90(mask,3)) # H = numpy.array([map(float,line.strip('\n').split(',')) for line in open('/Users/Goldmund/Documents/MATLAB/H.txt').readlines()]) print 'generate smear object' H = zeropad(strel(9, shape = 'disk'), mask.shape[0], mask.shape[1]) print 'broaden mask by blurring it' blurred = numpy.abs(myconv2(mask,H)) newMask = 1-(blurred<0.99) H2 = H print 'blurring new mask' newMask = numpy.abs(myconv2(newMask.astype('double'),H2)) mask *= newMask print 'creating gaussian and center mask' gMask = gaussian_mask(dimx,dimx,400,700,300) centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),150) return mask, gMask, centerMask
def display_APS_frames(frames, time_interval=1): ''' display DAVIS240 frames with fixed time interval inputs: frames : obtained from net_raw_UDP_jAER.py time_interval : optional parameter, time interval in between frames ''' plt.ion() my_obj = plt.imshow(plt.rot90(frames[1][3, :, :])) plt.hold('on') for i in range(len(frames)): frames[i][3, :, :] = frames[i][2, :, :] - frames[i][1, :, :] frames[i][6, :, :] = frames[i][5, :, :] - frames[i][4, :, :] frames[i][3, :, :][frames[i][3, :, :] < 0] = 0 my_obj.set_data(plt.rot90(frames[i][3, :, :])) plt.draw() sleep(1)
def montage(I): xdim, ydim, zdim = shape(I) nimages_x = int(ceil(sqrt(xdim))) nimages_y = int(ceil(sqrt(ydim))) nimages_z = int(ceil(sqrt(zdim))) Mx = zeros((nimages_x * zdim, nimages_x * ydim)) My = zeros((nimages_y * zdim, nimages_y * xdim)) Mz = zeros((nimages_z * ydim, nimages_z * xdim)) # Sagittal (x) # switch i2 and i1 for loops to have the slice sequence # progress vertically rather than horizontally. xcount = 0 for i1 in range(nimages_x): for i2 in range(nimages_x): xcount += 1 if xcount < xdim: Mx[ i1*zdim : (i1+1)*zdim, i2*ydim : (i2+1)*ydim ] = rot90(I[xdim-xcount,::-1,:],1) else: break # Coronal (y) ycount = 0 for i1 in range(nimages_y): for i2 in range(nimages_y): ycount += 1 if ycount < ydim: My[ i1*zdim : (i1+1)*zdim, i2*xdim : (i2+1)*xdim ] = flipud(I[::-1,ydim-ycount,:].transpose()) else: break # Horizontal (z) zcount = 0 for i1 in range(nimages_z): for i2 in range(nimages_z): zcount += 1 if zcount < zdim: Mz[ i1*ydim : (i1+1)*ydim, i2*xdim : (i2+1)*xdim ] = flipud(I[:,:,zdim-zcount].transpose()) else: break return Mx, My, Mz, xdim, ydim, zdim, nimages_x, nimages_y, nimages_z
def generate_masks(pattern, scattMaskRadius=50, scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=60): [dimy, dimx] = pattern.shape mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius) #mask[518:518+slit,:] = 0 #mask[370:480,520:650] = 0 #mask[:370,520:580] = 0 #mask[590:600,505:515] = 0 crosswidth = 10 shiftx = 10 shifty = 5 mask[512 - crosswidth + shiftx:512 + crosswidth + shiftx, :] = 0 mask[:, 512 - crosswidth + shifty:512 + crosswidth + shifty] = 0 mask[470:512, 400:512] = 0 mask = fliplr(rot90(mask, 3)) H = numpy.array([ map(float, line.strip('\n').split(',')) for line in filterwindow.split('\n') ]) blurred = imfilter(mask, H) newMask = 1 - (blurred < 0.99) H2 = H newMask = imfilter(newMask.astype('double'), H2) #newMask = imfilter(newMask.astype('double'), H2) mask *= newMask gMask = gaussian_mask(dimx, dimx, 400, 700, 300) centerMask = euclid(dimx, dimx, numpy.round(dimx / 2), numpy.round(dimx / 2), 90) return mask, gMask, centerMask
Mz3 = zeros((shape(Mz)[0], shape(Mz)[1], 3)) Mxyz = [Mx,My,Mz] Mxyz3 = [Mx3,My3,Mz3] dims1 = [shape(Mx)[0],shape(My)[0],shape(Mz)[0]] dims2 = [shape(Mx)[1],shape(My)[1],shape(Mz)[1]] for iaxis in range(3): M = Mxyz[iaxis] M3 = Mxyz3[iaxis] for i1 in range(dims1[iaxis]): for i2 in range(dims2[iaxis]): if str(int(M[i1,i2])) in labelnumbers: ilabel = labelnumbers.index(str(int(M[i1,i2]))) if labelnames[ilabel] not in exclude_list: labelcolor = labelcolors[ilabel].split(" ") rgb = (int(labelcolor[0]),int(labelcolor[1]),int(labelcolor[2])) M3[i1,i2,:] = rgb if iaxis == 0: Mx = M3 elif iaxis == 1: My = M3 elif iaxis == 2: Mz = M3 """ Save images (Alternatives:) pylab.imsave with: cmap=cm.gist_gray for grayscale or vmax=255 for color scipy.misc.toimage (http://www.scipy.org/Cookbook/Matplotlib/LoadImage) """ #plt.gray() imsave(out_path + '_x' + '.png', Mx) imsave(out_path + '_y' + '.png', My) imsave(out_path + '_z' + '.png', rot90(Mz,2))
def win(board, letter): wins = logical_or(board == letter, board == 'T') return any(all(wins, 0)) or any(all(wins, 1)) or all(diag(wins)) or \ all(diag(rot90(wins)))
estart = 0.0 deltae = 4.0 sqe = numpy.zeros((10,10), dtype='float') for iq in range(10): for ie in range(10): qtransfer = qstart + iq * deltaq etransfer = estart + ie * deltae sqe[iq,ie] = sqecalc.calcSqeCohCreateAllmodes(qtransfer, etransfer) print iq, ie, sqe[iq,ie] pickle.dump(sqe, open('sqe.pkl', 'w')) pylab.imshow(pylab.rot90(sqe)) pylab.show() end = raw_input() ######### #mp40 grid mp40=uc.getMonkhorstPackGrid((40,40,40)) sqecalc._kpts= mp40 sqecalc._numkpts = 64000 sqecalc.readIDFeigenvectors(filename='pols_FeAl222_mp40.idf') sqecalc.readEigenvaluesFromIDFomega2(filename='omega2_FeAl222_mp40.idf')